Plague Dot Text: Text mining and annotation of outbreak reports of the Third Plague Pandemic (1894-1952)

02/04/2020
by   Arlene Casey, et al.
0

The design of models that govern diseases in population is commonly built on information and data gathered from past outbreaks. However, epidemic outbreaks are never captured in statistical data alone but are communicated by narratives, supported by empirical observations. Outbreak reports discuss correlations between populations, locations and the disease to infer insights into causes, vectors and potential interventions. The problem with these narratives is usually the lack of consistent structure or strong conventions, which prohibit their formal analysis in larger corpora. Our interdisciplinary research investigates more than 100 reports from the third plague pandemic (1894-1952) evaluating ways of building a corpus to extract and structure this narrative information through text mining and manual annotation. In this paper we discuss the progress of our ongoing exploratory project, how we enhance optical character recognition (OCR) methods to improve text capture, our approach to structure the narratives and identify relevant entities in the reports. The structured corpus is made available via Solr enabling search and analysis across the whole collection for future research dedicated, for example, to the identification of concepts. We show preliminary visualisations of the characteristics of causation and differences with respect to gender as a result of syntactic-category-dependent corpus statistics. Our goal is to develop structured accounts of some of the most significant concepts that were used to understand the epidemiology of the third plague pandemic around the globe. The corpus enables researchers to analyse the reports collectively allowing for deep insights into the global epidemiological consideration of plague in the early twentieth century.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 4

page 6

page 7

page 10

page 14

page 15

05/23/2019

Exploring Diseases and Syndromes in Neurology Case Reports from 1955 to 2017 with Text Mining

Background: A large number of neurology case reports have been published...
03/29/2020

Named Entities in Medical Case Reports: Corpus and Experiments

We present a new corpus comprising annotations of medical entities in ca...
06/09/2020

EPIC: An Epidemics Corpus Of Over 20 Million Relevant Tweets

Since the start of COVID-19, several relevant corpora from various sourc...
06/09/2020

EPIC30M: An Epidemics Corpus Of Over 30 Million Relevant Tweets

Since the start of COVID-19, several relevant corpora from various sourc...
04/06/2020

Discovering associations in COVID-19 related research papers

A COVID-19 pandemic has already proven itself to be a global challenge. ...
09/10/2020

RadLex Normalization in Radiology Reports

Radiology reports have been widely used for extraction of various clinic...
08/31/2019

Extracting information from free text through unsupervised graph-based clustering: an application to patient incident records

The large volume of text in electronic healthcare records often remains ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.